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Record W2077444489 · doi:10.1080/09687630601111292

Evaluation of a media campaign aimed at preventing initiation into drug injection among street youth

2007· article· en· W2077444489 on OpenAlexaffabout
Élise Roy, Véronique Denis, Natalia Gutiérrez, Nancy Haley, Carole Morissette, Jean-François Boudreau

Bibliographic record

VenueDrugs Education Prevention and Policy · 2007
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversité de Sherbrooke
FundersMinistry of Education, India
KeywordsMedia campaignScope (computer science)Drug preventionMedicinePopulationPerceptionDrugInjection drug usePublic relationsEnvironmental healthAdvertisingPsychologyPolitical scienceSubstance abuseDrug injectionPharmacologyBusinessPsychiatry

Abstract

fetched live from OpenAlex

Aims: A campaign to prevent initiation into drug injecting among street youth who have never injected drugs (NIDUs) was carried out in Montréal, Canada in 2005. Evaluation objectives were (1) to assess the campaign's ability to reach NIDU street youth and (2) to understand the campaign's effects on this population.Methods: A survey was conducted, as well as semi-structured interviews.Findings: The campaign enjoyed a high degree of visibility. It spoke to young NIDUs, causing them to reflect on both drug injecting and their own non-injection drug use. The campaign had a positive impact in terms of their views on drug injecting. Despite its limited scope, young NIDUs also considered the campaign to be a tool with the potential to contribute to preventing initiation into drug injecting among their peers.Conclusions: Media prevention campaigns are able to reach hidden populations through the use of bold and innovative techniques. Such campaigns can also contribute to influencing the attitudes and perceptions of these populations. However, more comprehensive injection prevention programs need to be established.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.402
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2007
Admission routes2
Has abstractyes

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